Use of neural networks to recover from software faults in real-time systems

1994 ◽  
Author(s):  
Erwin L. Hunter ◽  
Abhijit S. Pandya ◽  
Neal Coulter
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Real Time Systems ◽  
Software Faults ◽  
Time Systems

scholarly journals Task-Level Re-Execution Framework for Improving Fault Tolerance on Symmetry Multiprocessors

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 651 ◽  
Author(s):  
Hyeongboo Baek ◽  
Jaewoo Lee
Keyword(s):  
Real Time ◽  
Fault Tolerant ◽  
Target System ◽  
Real Time Systems ◽  
Software Faults ◽  
Real Time Scheduling ◽  
Time Scheduling ◽  
Hard Real Time ◽  
Deployed Systems ◽  
Time Systems

Hard real-time systems are employed in military, aeronautics, and astronautics fields where deployed systems are susceptible to software faults that can result in functional errors. Thus, there is a need to use fault-tolerant (FT) real-time scheduling. Among the various fault-tolerant real-time scheduling techniques, re-execution has been applied widely to existing real-time systems owing to its simplicity and applicability. However, re-execution requires multiple executions of every task, and some tasks miss their deadlines owing to the prolonged execution time; therefore, it has been found to be suitable for only soft real-time systems. In this paper, we propose an FT policy that can be incorporated into most (if not all) existing real-time scheduling algorithms on multiprocessor systems, which improves the reliability of the target system without a tradeoff against schedulability. As a case study, we apply the FT policy to existing fixed-priority scheduling and earliest deadline zero-laxity scheduling, and we demonstrate that it enhances reliability without schedulability loss.

Timing isolation and improved scheduling of deep neural networks for real‐time systems

2020 ◽  
Vol 50 (9) ◽  
pp. 1760-1777 ◽  
Author(s):  
Daniel Casini ◽  
Alessandro Biondi ◽  
Giorgio Buttazzo
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Deep Neural Networks ◽  
Real Time Systems ◽  
Time Systems

New Hybrid Genetic Based Approach for Real-Time Scheduling of Reconfigurable Embedded Systems

2018 ◽  
Vol 10 (1) ◽  
pp. 23-36
Author(s):  
Ibrahim Gharbi ◽  
Hamza Gharsellaoui ◽  
Sadok Bouamama
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Scheduling Algorithm ◽  
Journal Article ◽  
Real Time Systems ◽  
Software Faults ◽  
Real Time Scheduling ◽  
Time Scheduling ◽  
Algorithmic Approaches ◽  
Time Systems

This journal article deals with the problem of real-time scheduling of operating systems (OS) tasks by a hybrid genetic-based scheduling algorithm. Indeed, most of real-time systems are framed with aid of priority-based scheduling algorithms. Nevertheless, when such a scenario is applied to save the system at the occurrence of hardware-software faults, or to improve its performance, some real-time properties can be violated at run-time. In contrast, most of the applications of real-time systems are based on timing constraints, i.e. OS tasks should be scheduled properly to finish their execution within the time specified by the real-time systems. For this reason, the authors propose in their article, a hybrid genetic-based scheduling approach that automatically checks the systems feasibility after any reconfiguration scenario was applied to an embedded system. A benchmark example is given, and the experimental results demonstrate the effectiveness of the originally proposed genetic-based scheduling approach over other such classical genetic algorithmic approaches.

Reconfiguration of Uniprocessor Sporadic Real-Time Systems

2011 ◽  
pp. 167-189 ◽  
Author(s):  
Laurent George ◽  
Pierre Courbin
Keyword(s):  
Sensitivity Analysis ◽  
Real Time ◽  
Performance Tuning ◽  
Real Time Systems ◽  
Software Faults ◽  
Worst Case ◽  
Task Model ◽  
Worst Case Execution Time ◽  
On Line ◽  
Time Systems

In this chapter the authors focus on the problem of reconfiguring embedded real-time systems. Such reconfiguration can be decided either off-line to determine if a given application can be run on a different platform, while preserving the timeliness constraints imposed by the application, or on-line, where a reconfiguration should be done to adapt the system to the context of execution or to handle hardware or software faults. The task model considered in this chapter is the classical sporadic task model defined by a Worst Case Execution Time (WCET), a minimum inter-arrival time (also denoted the minimum Period) and a late termination deadline. The authors consider two preemptive scheduling strategies: Fixed Priority highest priority first (FP) and Earliest Deadline First (EDF). They propose a sensitivity analysis to handle reconfiguration issues. Sensitivity analysis aims at determining acceptable deviations from the specifications of a problem due to evolutions in system characteristics (reconfiguration or performance tuning). They present a state of the art for sensitivity analysis in the case of WCETs, Periods and Deadlines reconfigurations and study to what extent sensitivity analysis can be used to decide on the possibility of reconfiguring a system.

VLSI Implementation of Neural Classifiers

1990 ◽  
Vol 2 (1) ◽  
pp. 35-43 ◽  
Author(s):  
Arun Rao ◽  
Mark R. Walker ◽  
Lawrence T. Clark ◽  
L. A. Akers ◽  
R. O. Grondin
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Associative Memory ◽  
Binary Classification ◽  
Real Time Systems ◽  
Classification Schemes ◽  
Pipelined Architecture ◽  
Hardware Implementations ◽  
Fixed Radius ◽  
Time Systems

The embedding of neural networks in real-time systems performing classification and clustering tasks requires that models be implemented in hardware. A flexible, pipelined associative memory capable of operating in real-time is proposed as a hardware substrate for the emulation of neural fixed-radius clustering and binary classification schemes. This paper points out several important considerations in the development of hardware implementations. As a specific example, it is shown how the ART1 paradigm can be functionally emulated by the limited resolution pipelined architecture, in the absence of full parallelism.

New Hybrid Genetic Based Approach for Real-Time Scheduling of Reconfigurable Embedded Systems

2021 ◽  
pp. 1140-1155
Author(s):  
Ibrahim Gharbi ◽  
Hamza Gharsellaoui ◽  
Sadok Bouamama
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Scheduling Algorithm ◽  
Journal Article ◽  
Real Time Systems ◽  
Software Faults ◽  
Real Time Scheduling ◽  
Time Scheduling ◽  
Algorithmic Approaches ◽  
Time Systems

This journal article deals with the problem of real-time scheduling of operating systems (OS) tasks by a hybrid genetic-based scheduling algorithm. Indeed, most of real-time systems are framed with aid of priority-based scheduling algorithms. Nevertheless, when such a scenario is applied to save the system at the occurrence of hardware-software faults, or to improve its performance, some real-time properties can be violated at run-time. In contrast, most of the applications of real-time systems are based on timing constraints, i.e. OS tasks should be scheduled properly to finish their execution within the time specified by the real-time systems. For this reason, the authors propose in their article, a hybrid genetic-based scheduling approach that automatically checks the systems feasibility after any reconfiguration scenario was applied to an embedded system. A benchmark example is given, and the experimental results demonstrate the effectiveness of the originally proposed genetic-based scheduling approach over other such classical genetic algorithmic approaches.

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